Identification of key genes associated with sepsis patients infected by staphylococcus aureus through weighted gene co-expression network analysis

• Published in: American journal of translational research Vol. 13; no. 12; pp. 13579 - 13589
• Main Authors: Wu, Han, Chen, Haoting, Wang, Junjie, Yin, Shaohua, Huang, Jiaqian, Wang, Zhiqiang, Zhang, Xiaojie, Wang, Minghua
• Format: Journal Article
• Language: English
• Published: United States e-Century Publishing Corporation 01-01-2021
• Subjects: Original; differential analysis; survival analysis; weighted gene coexpression network; Bacterial sepsis; staphylococcus aureus
• ISSN: 1943-8141; 1943-8141

The prevention and treatment of staphylococcus aureus septicemia is one of the thorniest problems in modern medicine. However, as the underlying pathogenesis of sepsis is still unclear, there is currently no golden standard for clinical diagnosis. In this study, we used GSE33341 dataset for differentially expressed gene (DEG) analysis and screened out 857 differentially expressed genes associated with staphylococcus aureus infection. The module having the highest correlation with clinical features of sepsis was screened by weighted gene co-expression network analysis (WGCNA). The genes in the selected module and the differentially expressed genes were represented in Venn diagram, and 59 pathogenic genes at the intersection were obtained. GO and KEGG analysis showed that these genes were mainly related to aerobic respiration, cellular stress response, mitochondrial electron transport, mitochondrial transport, oxidative phosphorylation. Kaplan-Meier was used to analyze the influence of the top 10 key genes on the prognosis of sepsis patients. The results showed that the high expression of NDUFA4, NDUFB3, COX7A2, ATP5J and COX7C was significantly correlated with the poor overall survival (OS) in patients with bacterial sepsis. These findings may potentially provide a reference for the diagnosis and treatment of bacterial septicemia.